Visualizing Investment Decision on Decision Balls
Author(s)
Li-Ching Ma*
Affiliation(s)
Department of Information Management, National United University, Miaoli, Taiwan, R.O.C..
Department of Information Management, National United University, Miaoli, Taiwan, R.O.C..
ABSTRACT
Decision makers’ choices are often influenced by visual background information. This study uses open-ended equity funds in Taiwan to investigate three well-known optimal portfolio models, including the mean-variance, maximin, and minimization of mean absolute deviation. The optimal portfolios are then visualized on Decision Balls to assist investors in making investment decisions. By observing the Decision Balls, investors can see the optimal portfolios, compare the optimal weights provided by the different models, view the cluster of funds, and even find substitute funds if preferred funds are not available.
Decision makers’ choices are often influenced by visual background information. This study uses open-ended equity funds in Taiwan to investigate three well-known optimal portfolio models, including the mean-variance, maximin, and minimization of mean absolute deviation. The optimal portfolios are then visualized on Decision Balls to assist investors in making investment decisions. By observing the Decision Balls, investors can see the optimal portfolios, compare the optimal weights provided by the different models, view the cluster of funds, and even find substitute funds if preferred funds are not available.
Cite this paper
nullL. Ma, "Visualizing Investment Decision on Decision Balls," American Journal of Operations Research, Vol. 1 No. 2, 2011, pp. 57-64. doi: 10.4236/ajor.2011.12009.
nullL. Ma, "Visualizing Investment Decision on Decision Balls," American Journal of Operations Research, Vol. 1 No. 2, 2011, pp. 57-64. doi: 10.4236/ajor.2011.12009.
References
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[1] I. Simonson and A. Tversky, “Choice in Context: Tradeoff Contrast and Extremeness Aversion,” Journal of Marketing Research, Vol. 29, No. 3, 1992, pp. 281-295. doi:10.2307/3172740 [2] L. M. Seiford and J. Zhu, “Context-Dependent Data Envelopment Analysis—Measuring Attractiveness and Progress,” Omega, Vol. 31, No. 5, 2003, pp. 397-408. doi:10.1016/S0305-0483(03)00080-X [3] A. Meyer, “Visual Data in Organizational Research,” Organization Science, Vol. 2, No. 2, 1991, pp. 218-236. [4] H. Markowitz, “Portfolio Selection,” Journal of Finance, Vol. 7, No. 1, 1952, pp. 77-91. doi:10.2307/2975974 [5] C. Genest and S. S. Zhang, “A Graphical Analysis of Ratio-Scaled Paired Comparison Data,” Management Science, Vol. 42, No. 3, 1996, pp. 335-349. doi:10.1287/mnsc.42.3.335 [6] L. C. Ma and H. L. Li, “Using Gower Plots And Decision Balls to Rank Alternatives Involving Inconsistent Preferences,” Decision Support Systems, Vol. 51, No. 3, 2011, pp. 712-719. doi:10.1016/j.dss.2011.04.004 [7] B. P. Gladish, D. F. Jones, M. Tamiz and A. B. Terol, “An Interactive Three-Stage Model for Mutual Funds Portfolio Selection,” Omega, Vol. 35, No. 1, 2007, pp. 75-88. doi:10.1016/j.omega.2005.04.003 [8] H. L. Li and L. C. Ma, “Visualizing Decision Processes on Spheres Based on the Even Swap Concept,” Decision Support Systems, Vol. 45, No. 2, 2008, pp. 354-367. [9] L. C. Ma, “Visualizing Preferences on Spheres for Group Decisions Based on Multiplicative Preference Relations,” European Journal of Operational Research, Vol. 203, No. 1, 2010, pp. 176-184. doi:10.1016/j.ejor.2009.07.008 [10] I. Borg and P. Groenen, “Modern Multidimensional Scaling,” Springer, New York., 1997. [11] T. F. Cox and M. A. A. Cox, “Multidimensional Scaling on a Sphere,” Communications on Statistics:Theory and Methods, Vol. 20, No. 9, 1991, pp. 2943-2953. doi:10.1080/03610929108830679 [12] W. S. Desarbo and K. Jedidi, “The Spatial Representation Of Heterogeneous Consideration Sets,” Marketing Science, Vol. 14, No. 3, pp. 326-342. doi:10.1287/mksc.14.3.326 [13] R. L. Andrews and A. K. Manrai, “MDS Maps For Product Attributes and Market Response: An Application to Scanner Panel Data,” Marketing Science, Vol. 18, No. 4, 1999, pp. 584-604. doi:10.1287/mksc.18.4.584 [14] P. G. Shu, Y. H. Yeh and T. Yamada, “The Behavior of Taiwan Mutual Fund Investors-Performance and Fund Flows,” Pacific-Basin Finance Journal, Vol. 10, No. 5, 2002, pp. 583-600. doi:10.1016/S0927-538X(02)00070-7 [15] C. S. Hsu, and J. R. Lin, “Mutual Fund Performance and Persistence in Taiwan: A Non-Parametric Approach,” The Service Industries Journal, Vol. 27, No. 5, 2007, pp. 509-523. doi:10.1080/02642060701411658 [16] M. R. Young, “A Minimax-Portfolio Selection Rule with Linear Programming Solution,” Management Science, Vol. 44, No. 5, 1998, pp. 673-683. doi:10.1287/mnsc.44.5.673 [17] H. Konno and H. Yamazaki, “Mean-absolute deviation portfolio optimization model and its application to Tokyo stock market,” Management Science, Vol. 37, No. 5, 1991, pp. 519-531. doi:10.1287/mnsc.37.5.519 [18] C. Papahristodoulou, and E. Dotzauer, “Optimal Portfolios Using Linear Programming Models,” Journal of the Operational Research Society, Vol. 55, No. 11, 2004, pp. 1169-1177. [19] T. F. Cox and M. A. A. Cox, Multidimensional Scaling. CRC Press, Boca Raton, 2000. doi:10.1201/9781420036121 [20] J. B. Kruskal, “Non-Metric Multidimensional Scaling: A Numerical Method,” Psychometrica, Vol. 29, No. 2, 1964, pp. 115-129. doi:10.1007/BF02289694